Triple

T11529322
Position Surface form Disambiguated ID Type / Status
Subject Zaleucus E273376 entity
Predicate legalCodeFeature P24436 FINISHED
Object fixed written statutes LITERAL FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: fixed written statutes | Statement: [Zaleucus, legalCodeFeature, fixed written statutes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: legalCodeFeature
Context triple: [Zaleucus, legalCodeFeature, fixed written statutes]
  • A. legalCodeAppliesTo
    Indicates that a particular legal code or statute is applicable to, or governs, a specified subject, situation, or entity.
  • B. legalCodeName
    Indicates that one entity is the official legal code designation or name assigned to another entity within a legal or regulatory system.
  • C. legalCodeAvailableAt
    Indicates that a particular legal code or statute can be accessed, obtained, or consulted at a specified source or location.
  • D. legalCodeType chosen
    Indicates the specific category or classification of a legal code that applies to an entity or situation.
  • E. legalCodeRecordedIn
    Indicates that a legal code is documented, registered, or officially stored within a particular record, system, or repository.
  • F. None of above.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6aae3fbec8190a14632a5df2538b6 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d883972b10819093bd09cf8406671c completed April 10, 2026, 4:59 a.m.
PD Predicate disambiguation batch_69d80879fdb48190be6dacc8aa63c809 completed April 9, 2026, 8:13 p.m.
Created at: April 8, 2026, 9:37 p.m.